Validated prediction of clinical outcome in sarcomas and multiple types of cancer on the basis of a gene expression signature related to genome complexity

Risk Stratification Tools to Aid Decisions on Adjuvant Chemotherapy Usage in Resected Soft Tissue Sarcomas: A Ten-Year Review of an Irish Sarcoma Center Experience

Background

Soft tissue sarcoma (STS) is comprised of approximately 80 subtypes, with an incidence of 4 - 5 per 100,000 annually in Europe. The National Comprehensive Cancer Network (NCCN) guidelines recommend consideration of neoadjuvant/adjuvant chemotherapy in tumors at high risk of recurrence based on the American Joint Committee on Cancer (AJCC) staging. Alternatively, the Sarculator is a risk prediction tool that has identified a threshold of risk, above which chemotherapy may provide an overall survival (OS) benefit. Using this nomogram, patients with a 10-year predicted OS < 60% are classified as high risk and should be considered for chemotherapy. The aim of this study was to assess the prognostic accuracy of these two risk prediction methods in an Irish population.

Methods

All newly diagnosed patients with resected STS discussed in the STS tumor board in Cork University Hospital between January 2012 and December 2021 were identified. Clinicopathological data were collected. Risk assessment using AJCC and Sarculator nomogram was performed on all patients with an extremity/trunk sarcoma. The OS was calculated including Kaplan-Meier method for time to event analysis.

Results

In total, 200 STS patients were reviewed, of whom 134 had truncal or extremity tumors. Sarculator score was calculated for 60 of these (well differentiated liposarcomas, desmoid tumors and dermatofibrosarcoma protuberans were excluded). Using the Sarculator nomogram to calculate 10-year predicted OS, 19 patients were categorized as high risk and 41 were categorized as low risk. Using AJCC staging, 25 patients were categorized as high risk and 35 as low risk. The 5-year OS rate in the Sarculator high-risk group was 60.2%, compared with 87.1% in the low-risk group (P = 0.009). The 5-year OS rate in the AJCC high-risk group was 67.6%, compared with 86.3% in the low-risk group (P = 0.083).

Conclusions

Our cohort is representative of the broad histological subtypes expected. In our population, Sarculator score results correlate with international outcomes and higher scores were associated with increased mortality. The Sarculator was more predictive of clinical outcome than AJCC staging, and its use would lower the proportion of patients being considered for adjuvant chemotherapy thereby sparing toxicity, which is important in the setting of uncertain clinical benefit.

Endometrioid Endometrial RNA Index Predicts Recurrence in Stage I Patients

PURPOSE

Risk prediction with genomic and transcriptomic data has the potential to improve patient outcomes by enabling clinicians to identify patients requiring adjuvant treatment approaches, while sparing low-risk patients from unnecessary interventions. Endometrioid endometrial carcinoma (EEC) is the most common cancer in women in developed countries, and rates of endometrial cancer are increasing.

EXPERIMENTAL DESIGN

We collected a 105-patient case-control cohort of stage I EEC comprising 45 patients who experienced recurrence less than 6 years after excision, and 60 Fédération Internationale de Gynécologie et d'Obstétrique grade-matched controls without recurrence. We first utilized two RNA-based, previously validated machine learning approaches, namely, EcoTyper and Complexity Index in Sarcoma (CINSARC). We developed Endometrioid Endometrial RNA Index (EERI), which uses RNA expression data from 46 genes to generate a personalized risk score for each patient. EERI was trained on our 105-patient cohort and tested on a publicly available cohort of 263 patients with stage I EEC.

RESULTS

EERI was able to predict recurrences with 94% accuracy in the training set and 81% accuracy in the test set. In the test set, patients assigned as EERI high-risk were significantly more likely to experience recurrence (30%) than the EERI low-risk group (1%) with a hazard ratio of 9.9 (95% CI, 4.1-23.8; P < 0.001).

CONCLUSIONS

Tumors with high-risk genetic features may require additional treatment or closer monitoring and are not readily identified using traditional clinicopathologic and molecular features. EERI performs with high sensitivity and modest specificity, which may benefit from further optimization and validation in larger independent cohorts.

Integration of pre-treatment computational radiomics, deep radiomics, and transcriptomics enhances soft-tissue sarcoma patient prognosis

Our objective was to capture subgroups of soft-tissue sarcoma (STS) using handcraft and deep radiomics approaches to understand their relationship with histopathology, gene-expression profiles, and metastatic relapse-free survival (MFS). We included all consecutive adults with newly diagnosed locally advanced STS (N = 225, 120 men, median age: 62 years) managed at our sarcoma reference center between 2008 and 2020, with contrast-enhanced baseline MRI. After MRI postprocessing, segmentation, and reproducibility assessment, 175 handcrafted radiomics features (h-RFs) were calculated. Convolutional autoencoder neural network (CAE) and half-supervised CAE (HSCAE) were trained in repeated cross-validation on representative contrast-enhanced slices to extract 1024 deep radiomics features (d-RFs). Gene-expression levels were calculated following RNA sequencing (RNAseq) of 110 untreated samples from the same cohort. Unsupervised classifications based on h-RFs, CAE, HSCAE, and RNAseq were built. The h-RFs, CAE, and HSCAE grouping were not associated with the transcriptomics groups but with prognostic radiological features known to correlate with lower survivals and higher grade and SARCULATOR groups (a validated prognostic clinical-histological nomogram). HSCAE and h-RF groups were also associated with MFS in multivariable Cox regressions. Combining HSCAE and transcriptomics groups significantly improved the prognostic performances compared to each group alone, according to the concordance index. The combined radiomic-transcriptomic group with worse MFS was characterized by the up-regulation of 707 genes and 292 genesets related to inflammation, hypoxia, apoptosis, and cell differentiation. Overall, subgroups of STS identified on pre-treatment MRI using handcrafted and deep radiomics were associated with meaningful clinical, histological, and radiological characteristics, and could strengthen the prognostic value of transcriptomics signatures.

Best Overall Response-Associated Signature to Doxorubicin in Soft Tissue Sarcomas: A Transcriptomic Analysis from ANNOUNCE

PURPOSE

This exploratory analysis evaluated the tumor samples of the patients treated with doxorubicin (with or without olaratumab) in a negative phase III ANNOUNCE trial to better understand the complexity of advanced soft tissue sarcomas (STS) and to potentially identify its predictive markers.

EXPERIMENTAL DESIGN

RNA sequencing was performed on pretreatment tumor samples (n = 273) from the ANNOUNCE trial to evaluate response patterns and identify potential predictive treatment markers for doxorubicin. A BOR-associated signature to doxorubicin (REDSARC) was created by evaluating tumors with radiographic response versus progression. An external cohort of doxorubicin-treated patients from the Spanish Group for Research on Sarcomas (GEIS) was used for refinement and validation.

RESULTS

A total of 259 samples from the trial were considered for analysis. Comparative analyses by the treatment arm did not explain the negative trial. However, there was an association between the BOR signature and histologic subtype (χ2P = 2.0e-7) and grade (P = 0.002). There were no associations between the BOR signature and gender, age, ethnicity, or stage. Applied to survival outcomes, REDSARC was also predictive for progression-free survival (PFS) and overall survival (OS). Using the GEIS cohort, a refined 25-gene signature was identified and applied to the ANNOUNCE cohort, where it was predictive of PFS and OS in leiomyosarcoma, liposarcoma, and other sarcoma subtypes, but not in undifferentiated pleomorphic sarcoma.

CONCLUSIONS

The refined REDSARC signature provides a potential tool to direct the application of doxorubicin in sarcomas and other malignancies. Validation and further refinement of the signature in other potentially subtype specific prospective cohorts is recommended.

TPX2 overexpression promotes sensitivity to dasatinib in breast cancer by activating YAP transcriptional signaling

Chromosomal instability (CIN) is a hallmark of cancer aggressiveness, providing genetic plasticity and tumor heterogeneity that allows the tumor to evolve and adapt to stress conditions. CIN is considered a cancer therapeutic biomarker because healthy cells do not exhibit CIN. Despite recent efforts to identify therapeutic strategies related to CIN, the results obtained have been very limited. CIN is characterized by a genetic signature where a collection of genes, mostly mitotic regulators, are overexpressed in CIN-positive tumors, providing aggressiveness and poor prognosis. We attempted to identify new therapeutic strategies related to CIN genes by performing a drug screen, using cells that individually express CIN-associated genes in an inducible manner. We find that the overexpression of targeting protein for Xklp2 (TPX2) enhances sensitivity to the proto-oncogene c-Src (SRC) inhibitor dasatinib due to activation of the Yes-associated protein 1 (YAP) pathway. Furthermore, using breast cancer data from The Cancer Genome Atlas (TCGA) and a cohort of cancer-derived patient samples, we find that both TPX2 overexpression and YAP activation are present in a significant percentage of cancer tumor samples and are associated with poor prognosis; therefore, they are putative biomarkers for selection for dasatinib therapy.

Establishing biomarkers for soft tissue sarcomas

INTRODUCTION

Soft tissue sarcomas (STS) are a rare and diverse group of tumors. Curative options are limited to localized disease, with surgery being the mainstay. Advanced stages are associated with a poor prognosis. Currently, the prognosis of the patient is based on histological classification and clinical characteristics, with only a few biomarkers having entered clinical practice.

AREAS COVERED

This article covers extensive recent research that has established novel potential biomarkers based on genomics, proteomics, and clinical characteristics. Validating and incorporating these biomarkers into clinical practice can improve prognosis, prediction of recurrence, and treatment response. Relevant literature was collected from PubMed, Scopus, and clinicaltrials.gov databases (November 2023).

EXPERT OPINION

Currently, defining prognostic markers in soft tissue sarcomas remains challenging. More studies are required, especially to personalize treatment through advanced genetic profiling and analysis using individual tumor and patient characteristics.

HMGA1 regulates trabectedin sensitivity in advanced soft-tissue sarcoma (STS): A Spanish Group for Research on Sarcomas (GEIS) study

HMGA1 is a structural epigenetic chromatin factor that has been associated with tumor progression and drug resistance. Here, we reported the prognostic/predictive value of HMGA1 for trabectedin in advanced soft-tissue sarcoma (STS) and the effect of inhibiting HMGA1 or the mTOR downstream pathway in trabectedin activity. The prognostic/predictive value of HMGA1 expression was assessed in a cohort of 301 STS patients at mRNA (n = 133) and protein level (n = 272), by HTG EdgeSeq transcriptomics and immunohistochemistry, respectively. The effect of HMGA1 silencing on trabectedin activity and gene expression profiling was measured in leiomyosarcoma cells. The effect of combining mTOR inhibitors with trabectedin was assessed on cell viability in vitro studies, whereas in vivo studies tested the activity of this combination. HMGA1 mRNA and protein expression were significantly associated with worse progression-free survival of trabectedin and worse overall survival in STS. HMGA1 silencing sensitized leiomyosarcoma cells for trabectedin treatment, reducing the spheroid area and increasing cell death. The downregulation of HGMA1 significantly decreased the enrichment of some specific gene sets, including the PI3K/AKT/mTOR pathway. The inhibition of mTOR, sensitized leiomyosarcoma cultures for trabectedin treatment, increasing cell death. In in vivo studies, the combination of rapamycin with trabectedin downregulated HMGA1 expression and stabilized tumor growth of 3-methylcholantrene-induced sarcoma-like models. HMGA1 is an adverse prognostic factor for trabectedin treatment in advanced STS. HMGA1 silencing increases trabectedin efficacy, in part by modulating the mTOR signaling pathway. Trabectedin plus mTOR inhibitors are active in preclinical models of sarcoma, downregulating HMGA1 expression levels and stabilizing tumor growth.

Sarcoma microenvironment cell states and ecosystems are associated with prognosis and predict response to immunotherapy

Characterization of the diverse malignant and stromal cell states that make up soft tissue sarcomas and their correlation with patient outcomes has proven difficult using fixed clinical specimens. Here, we employed EcoTyper, a machine-learning framework, to identify the fundamental cell states and cellular ecosystems that make up sarcomas on a large scale using bulk transcriptomes with clinical annotations. We identified and validated 23 sarcoma-specific, transcriptionally defined cell states, many of which were highly prognostic of patient outcomes across independent datasets. We discovered three conserved cellular communities or ecotypes associated with underlying genomic alterations and distinct clinical outcomes. We show that one ecotype defined by tumor-associated macrophages and epithelial-like malignant cells predicts response to immune-checkpoint inhibition but not chemotherapy and validate our findings in an independent cohort. Our results may enable identification of patients with soft tissue sarcomas who could benefit from immunotherapy and help develop new therapeutic strategies.

Case Series of Soft Tissue Sarcoma Patients with Brain Metastasis with Implications from Genomic and Transcriptomic Analysis

PURPOSE

Brain metastasis rarely occurs in soft tissue sarcoma (STS). Here, we present five cases of STS with brain metastases with genetic profiles.

MATERIALS AND METHODS

We included five patients from Seoul National University Hospital who were diagnosed with STS with metastasis to the brain. Tissue from the brain metastasis along with that from the primary site or other metastases were used for DNA and RNA sequencing to identify genetic profiles. Gene expression profiles were compared with sarcoma samples from The Cancer Genome Atlas.

RESULTS

The overall survival after diagnosis of brain metastasis ranged from 2.2 to 34.3 months. Comparison of mutational profiles between brain metastases and matched primary or other metastatic samples showed similar profiles. In two patients, copy number variation profiles between brain metastasis and other tumors showed several differences including MYCL, JUN, MYC, and DDR2 amplification. Gene ontology analysis showed that the group of genes significantly highly expressed in the brain metastasis samples was enriched in the G-protein coupled receptor activity, structural constituent of chromatin, protein heterodimerization activity, and binding of DNA, RNA, and protein. Gene set enrichment analysis showed enrichment in the pathway of neuroactive ligand-receptor interaction and systemic lupus erythematosus.

CONCLUSION

The five patients had variable ranges of clinical courses and outcomes. Genomic and transcriptomic analysis of STS with brain metastasis implicates possible involvement of complex expression modification and epigenetic changes rather than the addition of single driver gene alteration.

Opportunity in Complexity: Harnessing Molecular Biomarkers and Liquid Biopsies for Personalized Sarcoma Care

Due to their rarity and complexity, sarcomas represent a substantial therapeutic challenge. However, the incredible diversity within and across sarcoma subtypes presents an opportunity for personalized care to maximize efficacy and limit toxicity. A deeper understanding of the molecular alterations that drive sarcoma development and treatment response has paved the way for molecular biomarkers to shape sarcoma treatment. Genetic, transcriptomic, and protein biomarkers have become critical tools for diagnosis, prognostication, and treatment selection in patients with sarcomas. In the future, emerging biomarkers like circulating tumor DNA analysis offer the potential to improve early detection, monitoring response to treatment, and identifying mechanisms of resistance to personalize sarcoma treatment. Here, we review the current state of molecular biomarkers for sarcomas and highlight opportunities and challenges for the implementation of new technologies in the future.

Current updates in sarcoma biomarker discovery: emphasis on next-generation sequencing-based methods

Soft tissue sarcomas comprise a heterogeneous group of neoplasms. Although soft tissue malignancies make up only 2% of adult cancers, classification based on histomorphology presents a diagnostic challenge. Characterisation of soft tissue sarcomas by molecular analysis is rapidly evolving to improve diagnostic accuracy and develop targeted therapies. This review highlights the advances in molecular techniques, including current next-generation sequencing-based assays (fusion detection by RNA sequencing, targeted/whole exome sequencing, microRNA profiling), as well as emerging methods (liquid biopsies, DNA methylation profiling, single-cell molecular profiling and next-generation immunohistochemistry) for future clinical applications.

Sarcoma cell-specific radiation sensitization by titanate scrolled nanosheets: insights from physicochemical analysis and transcriptomic profiling

This study aimed to explore the potential of metal oxides such as Titanate Scrolled Nanosheets (TNs) in improving the radiosensitivity of sarcoma cell lines. Enhancing the response of cancer cells to radiation therapy is crucial, and one promising approach involves utilizing metal oxide nanoparticles. We focused on the impact of exposing two human sarcoma cell lines to both TNs and ionizing radiation (IR). Our research was prompted by previous in vitro toxicity assessments, revealing a correlation between TNs' toxicity and alterations in intracellular calcium homeostasis. A hydrothermal process using titanium dioxide powder in an alkaline solution produced the TNs. Our study quantified the intracellular content of TNs and analyzed their impact on radiation-induced responses. This assessment encompassed PIXE analysis, cell proliferation, and transcriptomic analysis. We observed that sarcoma cells internalized TNs, causing alterations in intracellular calcium homeostasis. We also found that irradiation influence intracellular calcium levels. Transcriptomic analysis revealed marked disparities in the gene expression patterns between the two sarcoma cell lines, suggesting a potential cell-line-dependent nano-sensitization to IR. These results significantly advance our comprehension of the interplay between TNs, IR, and cancer cells, promising potential enhancement of radiation therapy efficiency.

Selective DNA-PK Inhibition Enhances Chemotherapy and Ionizing Radiation Activity in Soft-Tissue Sarcomas

PURPOSE

Patients with advanced soft-tissue sarcomas (STS) exhibit a poor prognosis and have few therapeutic options. DNA-dependent protein kinase (DNA-PK) catalytic subunit is a multifunctional serine-threonine protein kinase that plays a crucial role in DNA double-strand damage repair via nonhomologous end joining.

EXPERIMENTAL DESIGN

To investigate the therapeutic potential of DNA-PK targeting in STS, we first evaluated the prognostic value of DNA-PK expression in two large cohorts of patients with STS. We then used the potent and selective DNA-PK inhibitor AZD7648 compound to investigate the antitumor effect of the pharmacologic inhibition of DNA-PK in vitro via MTT, apoptosis, cell cycle, and proliferation assays. In vivo studies were performed with patient-derived xenograft models to evaluate the effects of AZD7648 in combination with chemotherapy or ionizing radiation on tumor growth. The mechanisms of sensitivity and resistance to DNA-PK inhibition were investigated by using a genome-wide CRISPR-Cas9 positive screen.

RESULTS

DNA-PK overexpression is significantly associated with poor prognosis in patients with sarcomas. Selective pharmacologic inhibition of DNA-PK strongly synergizes with radiation- and doxorubicin-based regimen in sarcoma models. By using a genome-wide CRISPR-Cas9 positive screen, we identified genes involved in sensitivity to DNA-PK inhibition.

CONCLUSIONS

DNA-PK inhibition deserves clinical investigation to improve response to current therapies in patients with sarcoma.

Management of oligometastatic/metastatic sarcomas and place of local treatments with focus on modern radiotherapy approaches

Soft tissue sarcomas are a rare and heterogeneous disease. For localized disease, treatment is based on surgery and radiotherapy with or without chemotherapy depending on risk factors. Upfront metastases are present in 7 to 20% of cases, and are localized to the lungs in most of cases. Disseminated disease is generally considered incurable but in selected cases, aggressive local treatment of metastases allowed long survival. Treatment of primary tumour is often debated. Our purpose is to evaluate the literature concerning the role of radiotherapy in the management of primary metastatic soft tissue sarcomas.

Deciphering the correlation between metabolic activity through 18F-FDG-PET/CT and immune landscape in soft-tissue sarcomas: an insight from the NEOSARCOMICS study

Metabolic elevation in soft-tissue sarcomas (STS), as documented with 18F-Fluorodeoxyglucose positron emission tomography (18F-FDG-PET/CT) has been linked with cell proliferation, higher grade, and lower survivals. However, the recent diagnostic innovations (CINSARC gene-expression signature and tertiary lymphoid structure [TLS]) and therapeutic innovations (immune checkpoint inhibitors [ICIs]) for STS patients underscore the need to re-assess the role of 18F-FDG-PET/CT. Thus, in this correspondence, our objective was to investigate the correlations between STS metabolism as assessed by nuclear imaging, and the immune landscape as estimated by transcriptomics analysis, immunohistochemistry panels, and TLS assessment. Based on a prospective cohort of 85 adult patients with high-grade STS recruited in the NEOSARCOMICS trial (NCT02789384), we identified 3 metabolic groups according to 18F-FDG-PET/CT metrics (metabolic-low [60%], -intermediate [15.3%] and high [24.7%]). We found that T-cells CD8 pathway was significantly enriched in metabolic-high STS. Conversely, several pathways involved in antitumor immune response, cell differentiation and cell cycle, were downregulated in extreme metabolic-low STS. Next, multiplex immunofluorescence showed that densities of CD8+, CD14+, CD45+, CD68+, and c-MAF cells were significantly higher in the metabolic-high group compared to the metabolic-low group. Lastly, no association was found between metabolic group and TLS status. Overall, these results suggest that (i) rapidly proliferating and metabolically active STS can instigate a more robust immune response, thereby attracting immune cells such as T cells and macrophages, and (ii) metabolic activity and TLS could independently influence immune responses.

Diagnostic accuracy and safety of percutaneous core needle biopsy of retroperitoneal tumours

BACKGROUND

Histologic subtype of cancer guides treatment sequencing and the extent of surgery for retroperitoneal tumours (RPTs) but concerns persist regarding percutaneous core needle biopsy (CNB).

OBJECTIVE

Endpoints were the incidence of early complications, needle tract seeding (NTS) after CNB, diagnostic accuracy.

METHODS

Between 2015 and 2022, data from patients with RPT who underwent a CNB and who operated on at Institut Curie were collected. We retrospectively reviewed the medical records and microscopic analysis of both CNB and surgical specimens to evaluate the diagnostic accuracy of CNB (quantified using positive and negative predictive values, PPV/NPV).

RESULTS

313 patients underwent CNB. In 10/326 (3 %) procedures, minor complications were observed. One of 212 (0.47 %) resected RPSs exhibited a local recurrence compatible with NTS. Microscopic analysis of CNB specimens allowed the classification of tumours between groups of cancers and benign/intermediate mesenchymal tumours in 307/313 (98 %) patients. Among the 204 patients with retroperitoneal sarcoma, the overall concordance between CNB and final pathology following resection was 178/204 (87.2 %). The respective PPVs of solitary fibrous tumour, dedifferentiated liposarcoma, leiomyosarcoma and well-differentiated liposarcoma were 100 %, 98 %, 97 % and 68 %, respectively. The diagnosis of a high-grade (G 2-3) sarcoma resulted in a high specificity (97 %) and PPV (98 %) but low sensitivity (76 %).

CONCLUSIONS

CNB allowed the classification of RPT in the vast majority of patients with a low morbidity rate. Concordance with final diagnosis was high for sarcomas with the exception of well-differentiated liposarcoma. As a result, CNB results should be integrated with imaging/radiomics by multidisciplinary tumour boards.

Radiomics and artificial intelligence for soft-tissue sarcomas: Current status and perspectives

This article proposes a summary of the current status of the research regarding the use of radiomics and artificial intelligence to improve the radiological assessment of patients with soft tissue sarcomas (STS), a heterogeneous group of rare and ubiquitous mesenchymal malignancies. After a first part explaining the principle of radiomics approaches, from raw image post-processing to extraction of radiomics features mined with unsupervised and supervised machine-learning algorithms, and the current research involving deep learning algorithms in STS, especially convolutional neural networks, this review details their main research developments since the formalisation of 'radiomics' in oncologic imaging in 2010. This review focuses on CT and MRI and does not involve ultrasonography. Radiomics and deep radiomics have been successfully applied to develop predictive models to discriminate between benign soft-tissue tumors and STS, to predict the histologic grade (i.e., the most important prognostic marker of STS), the response to neoadjuvant chemotherapy and/or radiotherapy, and the patients' survivals and probability for presenting distant metastases. The main findings, limitations and expectations are discussed for each of these outcomes. Overall, after a first decade of publications emphasizing the potential of radiomics through retrospective proof-of-concept studies, almost all positive but with heterogeneous and often non-replicable methods, radiomics is now at a turning point in order to provide robust demonstrations of its clinical impact through open-science, independent databases, and application of good and standardized practices in radiomics such as those provided by the Image Biomarker Standardization Initiative, without forgetting innovative research paths involving other '-omics' data to better understand the relationships between imaging of STS, gene-expression profiles and tumor microenvironment.

Sarcoma care in the era of precision medicine

Sarcoma subtype classification is currently mainly based upon histopathological morphology. Molecular analyses have emerged as an efficient addition to the diagnostic workup and sarcoma care. Knowledge about the sarcoma genome increases, and genetic events that can either support a histopathological diagnosis or suggest a differential diagnosis are identified, as well as novel therapeutic targets. In this review, we present diagnostic, therapeutic, and prognostic molecular markers that are, or might soon be, used clinically. For sarcoma diagnostics, there are specific fusions highly supportive or pathognomonic for a diagnostic entity-for instance, SYT::SSX in synovial sarcoma. Complex karyotypes also give diagnostic information-for example, supporting dedifferentiation rather than low-grade central osteosarcoma or well-differentiated liposarcoma when detected in combination with MDM2/CDK4 amplification. Molecular treatment predictive sarcoma markers are available for gastrointestinal stromal tumor (GIST) and locally aggressive benign mesenchymal tumors. The molecular prognostic markers for sarcomas in clinical practice are few. For solitary fibrous tumor, the type of NAB2::STAT6 fusion is associated with the outcome, and the KIT/PDGFRA pathogenic variant in GISTs can give prognostic information. With the exploding availability of sequencing technologies, it becomes increasingly important to understand the strengths and limitations of those methods and their context in sarcoma diagnostics. It is reasonable to believe that most sarcoma treatment centers will increase the use of massive-parallel sequencing soon. We conclude that the context in which the genetic findings are interpreted is of importance, and the interpretation of genomic findings requires considering tumor histomorphology.

Genomic Profiling and Clinical Outcomes of Targeted Therapies in Adult Patients with Soft Tissue Sarcomas

Genomic profiling has improved our understanding of the pathogenesis of different cancers and led to the development of several targeted therapies, especially in epithelial tumors. In this review, we focus on the clinical utility of next-generation sequencing (NGS) to inform therapeutics in soft tissue sarcoma (STS). The role of NGS is still controversial in patients with sarcoma, given the low mutational burden and the lack of recurrent targetable alterations in most of the sarcoma histotypes. The clinical impact of genomic profiling in STS has not been investigated prospectively. A limited number of retrospective, mainly single-institution, studies have addressed this issue using various NGS technologies and platforms and a variety of criteria to define a genomic alteration as actionable. Despite the detailed reports on the different gene mutations, fusions, or amplifications that were detected, data on the use and efficacy of targeted treatment are very scarce at present. With the exception of gastrointestinal stromal tumors (GISTs), these targeted therapies are administered either through off-label prescription of an approved drug or enrollment in a matched clinical trial. Based mainly on anecdotal reports, the outcome of targeted therapies in the different STS histotypes is discussed. Prospective studies are warranted to assess whether genomic profiling improves the management of STS patients.

Risk Factors for the Development of Early Recurrence in Patients with Primary Retroperitoneal Sarcoma

BACKGROUND

Disease recurrence after retroperitoneal sarcoma (RPS) surgery is common, and resection may offer no benefit for patients who experience recurrence early. This study examined the incidence of early recurrence (EREC) in RPS patients, and the association between EREC and prognosis, aiming to identify the factors associated with EREC.

METHODS

Patients undergoing surgery for primary RPS from 2008 to 2019 at two tertiary RPS centers were analyzed. The study defined EREC as any evidence of local recurrence and/or distant metastases on the CT scan up to 6 months after surgery. Overall survival (OS) was calculated using the Kaplan-Meier method. A multivariable analysis was performed to identify independent predictors of EREC.

RESULTS

Of the 692 patients who underwent surgery during the study period, 657 were included in the analysis. Sixty-five of these patients (9.9%; 95% confidence interval [CI], 7.7-12.4%) developed EREC. Five-year OS was 3% for the patients with EREC versus 76% for those without EREC (p < 0.001). Patient characteristics were compared between the EREC and non-EREC patients, and EREC was found to be significantly associated with Eastern Cooperative Oncology Group (ECOG) performance status (p = 0.006), tumor histology (p = 0.002), tumor grading (p < 0.001), radiotherapy (p = 0.04), and postoperative complications measured as a comprehensive complications index value (p = 0.003). However, the only significant independent predictor of EREC in the multivariable analysis was grade 3 tumors, with an odds ratio of 14.8 (95% CI, 4.44-49.2; p < 0.001).

CONCLUSION

Early recurrence is associated with a poor prognosis, and a high tumor grade is an independent predictor for the development of EREC. Patients with EREC may benefit the most from new therapeutic options such as neoadjuvant chemotherapy.

A pan-sarcoma landscape of telomeric content shows that alterations in RAD51B and GID4 are associated with higher telomeric content

Tumor cells need to activate a telomere maintenance mechanism, enabling limitless replication. The bulk of evidence supports that sarcomas predominantly use alternative lengthening of telomeres (ALT) mechanism, commonly associated with alterations in ATRX and DAXX. In our dataset, only 12.3% of sarcomas harbored alterations in these genes. Thus, we checked for the presence of other genomic determinants of high telomeric content in sarcomas. Our dataset consisted of 13555 sarcoma samples, sequenced as a part of routine clinical care on the FoundationOne®Heme platform. We observed a median telomeric content of 622.3 telomeric reads per GC-matched million reads (TRPM) across all samples. In agreement with previous studies, telomeric content was significantly higher in ATRX altered and POT1 altered sarcomas. We further observed that sarcomas with alterations in RAD51B or GID4 were enriched in samples with high telomeric content, specifically within uterus leiomyosarcoma for RAD51B and soft tissue sarcoma (not otherwise specified, nos) for GID4, Furthermore, RAD51B and POT1 alterations were mutually exclusive with ATRX and DAXX alterations, suggestive of functional redundancy. Our results propose a role played by RAD51B and GID4 in telomere elongation in sarcomas and open research opportunities for agents aimed at targeting this critical pathway in tumorigenesis.

Heterogeneity in the gene regulatory landscape of leiomyosarcoma

Characterizing inter-tumor heterogeneity is crucial for selecting suitable cancer therapy, as the presence of diverse molecular subgroups of patients can be associated with disease outcome or response to treatment. While cancer subtypes are often characterized by differences in gene expression, the mechanisms driving these differences are generally unknown. We set out to model the regulatory mechanisms driving sarcoma heterogeneity based on patient-specific, genome-wide gene regulatory networks. We developed a new computational framework, PORCUPINE, which combines knowledge on biological pathways with permutation-based network analysis to identify pathways that exhibit significant regulatory heterogeneity across a patient population. We applied PORCUPINE to patient-specific leiomyosarcoma networks modeled on data from The Cancer Genome Atlas and validated our results in an independent dataset from the German Cancer Research Center. PORCUPINE identified 37 heterogeneously regulated pathways, including pathways representing potential targets for treatment of subgroups of leiomyosarcoma patients, such as FGFR and CTLA4 inhibitory signaling. We validated the detected regulatory heterogeneity through analysis of networks and chromatin states in leiomyosarcoma cell lines. We showed that the heterogeneity identified with PORCUPINE is not associated with methylation profiles or clinical features, thereby suggesting an independent mechanism of patient heterogeneity driven by the complex landscape of gene regulatory interactions.

The spectrum and significance of secondary (co-occurring) genetic alterations in sarcomas: the hallmarks of sarcomagenesis

Bone and soft tissue tumors are generally classified into complex karyotype sarcomas versus those with recurrent genetic alterations, often in the form of gene fusions. In this review, we provide an overview of important co-occurring genomic alterations, organized by biological mechanisms and covering a spectrum of genomic alteration types: mutations (single-nucleotide variations or indels) in oncogenes or tumor suppressor genes, copy number alterations, transcriptomic signatures, genomic complexity indices (e.g. CINSARC), and complex genomic structural variants. We discuss the biological and prognostic roles of these so-called secondary or co-occurring alterations, arguing that recognition and detection of these alterations may be significant for our understanding and management of mesenchymal tumors. On a related note, we also discuss major recurrent alterations in so-called complex karyotype sarcomas. These secondary alterations are essential to sarcomagenesis via a variety of mechanisms, such as inactivation of tumor suppressors, activation of proliferative signal transduction, telomere maintenance, and aberrant regulation of epigenomic/chromatin remodeling players. The use of comprehensive genomic profiling, including targeted next-generation sequencing panels or whole-exome sequencing, may be incorporated into clinical workflows to offer more comprehensive, potentially clinically actionable information. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Distinct mechanisms of PTEN inactivation in dogs and humans highlight convergent molecular events that drive cell division in the pathogenesis of osteosarcoma

A hallmark of osteosarcoma in both human and canine tumors is somatic fragmentation and rearrangement of chromosome structure which leads to recurrent increases and decreases in DNA copy number. The PTEN gene has been implicated as an important tumor suppressor in osteosarcoma via forward genetic screens. Here, we analyzed copy number changes, promoter methylation and transcriptomes to better understand the role of PTEN in canine and human osteosarcoma. Reduction in PTEN copy number was observed in 23 of 95 (25%) of the canine tumors examined leading to corresponding decreases in PTEN transcript levels from RNA-Seq samples. Unexpectedly, canine tumors with an intact PTEN locus had higher levels of PTEN transcripts than human tumors. This variation in transcript abundance was used to evaluate the role of PTEN in osteosarcoma biology. Decreased PTEN copy number and transcript level was observed in - and likely an important driver of - increases in cell cycle transcripts in four independent canine transcriptional datasets. In human osteosarcoma, homozygous copy number loss was not observed, instead increased methylation of the PTEN promoter was associated with increased cell cycle transcripts. Somatic modification of PTEN, either by homozygous deletion in dogs or by promoter methylation in humans, is clinically relevant to osteosarcoma, because the cell cycle related transcripts are associated with patient outcomes. The PTEN gene is part of a syntenic rearrangement unique to the canine genome, making it susceptible to somatic loss of both copies of distal chromosome 26 which also includes the FAS death receptor. SIGNIFICANCE STATEMENT: PTEN function is abrogated by different mechanisms in canine and human osteosarcoma tumors leading to uncontrolled cell cycling. Somatic loss of this canine specific syntenic region may help explain why the canine genome appears to be uniquely susceptible to osteosarcoma. Syntenic arrangement, in the context of copy number change, may lead to synergistic interactions that in turn modify species specific cancer risk. Comparative models of tumorigenesis may utilize different driver mechanisms.

Analysis of the Peritumoral Tissue Unveils Cellular Changes Associated with a High Risk of Recurrence

BACKGROUND

The management of soft-tissue sarcoma (STS) relies on a multidisciplinary approach involving specialized oncological surgery combined with other adjuvant therapies to achieve optimal local disease control. Purpose and Results: Genomic and transcriptomic pseudocapsules of 20 prospective sarcomas were analyzed and revealed to be correlated with a higher risk of recurrence after surgery.

CONCLUSIONS

A peritumoral environment that has been remodeled and infiltrated by M2 macrophages, and is less expressive of healthy tissue, would pose a significant risk of relapse and require more aggressive treatment strategies.

The proteomic landscape of soft tissue sarcomas

Soft tissue sarcomas (STS) are rare and diverse mesenchymal cancers with limited treatment options. Here we undertake comprehensive proteomic profiling of tumour specimens from 321 STS patients representing 11 histological subtypes. Within leiomyosarcomas, we identify three proteomic subtypes with distinct myogenesis and immune features, anatomical site distribution and survival outcomes. Characterisation of undifferentiated pleomorphic sarcomas and dedifferentiated liposarcomas with low infiltrating CD3 + T-lymphocyte levels nominates the complement cascade as a candidate immunotherapeutic target. Comparative analysis of proteomic and transcriptomic profiles highlights the proteomic-specific features for optimal risk stratification in angiosarcomas. Finally, we define functional signatures termed Sarcoma Proteomic Modules which transcend histological subtype classification and show that a vesicle transport protein signature is an independent prognostic factor for distant metastasis. Our study highlights the utility of proteomics for identifying molecular subgroups with implications for risk stratification and therapy selection and provides a rich resource for future sarcoma research.

An OMA1 redox site controls mitochondrial homeostasis, sarcoma growth, and immunogenicity

Aggressive tumors often display mitochondrial dysfunction. Upon oxidative stress, mitochondria undergo fission through OMA1-mediated cleavage of the fusion effector OPA1. In yeast, a redox-sensing switch participates in OMA1 activation. 3D modeling of OMA1 comforted the notion that cysteine 403 might participate in a similar sensor in mammalian cells. Using prime editing, we developed a mouse sarcoma cell line in which OMA1 cysteine 403 was mutated in alanine. Mutant cells showed impaired mitochondrial responses to stress including ATP production, reduced fission, resistance to apoptosis, and enhanced mitochondrial DNA release. This mutation prevented tumor development in immunocompetent, but not nude or cDC1 dendritic cell-deficient, mice. These cells prime CD8+ lymphocytes that accumulate in mutant tumors, whereas their depletion delays tumor control. Thus, OMA1 inactivation increased the development of anti-tumor immunity. Patients with complex genomic soft tissue sarcoma showed variations in the level of OMA1 and OPA1 transcripts. High expression of OPA1 in primary tumors was associated with shorter metastasis-free survival after surgery, and low expression of OPA1, with anti-tumor immune signatures. Targeting OMA1 activity may enhance sarcoma immunogenicity.

New developments in the pathology and molecular biology of retroperitoneal sarcomas

Retroperitoneal sarcomas (RPS) refer to a heterogeneous group of malignancies of mesenchymal origin developing from retroperitoneal tissues and vessels. The most frequent RPS are well differentiated/dedifferentiated liposarcomas and leiomyosarcomas, but other rare histological subtypes can be observed. Over the last decade, significant advances have been made in the pathological and molecular characterization of sarcomas. These advances have led to major changes in their diagnostic management as well as in the development of new therapeutic strategies based on tumor biology and microenvironment. This review describes the current knowledge and recent findings in the pathology and molecular biology of the most frequent RPS subtypes.

Technical development and validation of a clinically applicable microenvironment classifier as a biomarker of tumour hypoxia for soft tissue sarcoma

BACKGROUND

Soft tissue sarcomas (STS) are rare, heterogeneous tumours and biomarkers are needed to inform management. We previously derived a prognostic tumour microenvironment classifier (24-gene hypoxia signature). Here, we developed/validated an assay for clinical application.

METHODS

Technical performance of targeted assays (Taqman low-density array, nanoString) was compared in 28 prospectively collected formalin-fixed, paraffin-embedded (FFPE) biopsies. The nanoString assay was biologically validated by comparing to HIF-1α/CAIX immunohistochemistry (IHC) in clinical samples. The Manchester (n = 165) and VORTEX Phase III trial (n = 203) cohorts were used for clinical validation. The primary outcome was overall survival (OS).

RESULTS

Both assays demonstrated excellent reproducibility. The nanoString assay detected upregulation of the 24-gene signature under hypoxia in vitro, and 16/24 hypoxia genes were upregulated in tumours with high CAIX expression in vivo. Patients with hypoxia-high tumours had worse OS in the Manchester (HR 3.05, 95% CI 1.54-5.19, P = 0.0005) and VORTEX (HR 2.13, 95% CI 1.19-3.77, P = 0.009) cohorts. In the combined cohort, it was independently prognostic for OS (HR 2.24, 95% CI 1.42-3.53, P = 0.00096) and associated with worse local recurrence-free survival (HR 2.17, 95% CI 1.01-4.68, P = 0.04).

CONCLUSIONS

This study comprehensively validates a microenvironment classifier befitting FFPE STS biopsies. Future uses include: (1) selecting high-risk patients for perioperative chemotherapy; and (2) biomarker-driven trials of hypoxia-targeted therapies.

EJSO educational Special issue from the TARPSWG - Standard medical treatment and new options in retroperitoneal sarcoma

Retroperitoneal soft tissue sarcomas mainly consist histologically of liposarcomas and leiomyosarcomas. For the liposarcoma subgroup, the local relapse rate seems to determine patients' overall prognosis. In contrast, leiomyosarcoma patients are challenged by the development of metastatic disease; therefore, effective systemic therapies are the cornerstone to improve patients' outcome. No doubt, the limited number of active regimens currently available makes the treatment of patients with locally advanced and/or metastatic disease challenging and results in the overall poor prognosis of this population. In this European Journal of Surgical Oncology Educational Special Issue from the Transatlantic Australasian RetroPeritoneal Sarcoma Working Group (TARPSWG), we aim to summarize state-of-the-art systemic treatments for patients with retroperitoneal sarcomas with a focus on the locally advanced and metastatic disease setting including conventional standard chemotherapies as well as new innovative treatment approaches in order to identify current unmet medical needs guiding the sarcoma community to initiate appropriate translational research projects and design innovative clinical trials.

Genome-wide CRISPR/Cas9 library screening identified ATM signaling network genes as critical drivers for resistance to ATR inhibition in soft-tissue sarcomas: synthetic lethality and therapeutic implications

Soft-tissue sarcoma (STS) are a heterogeneous group of rare tumors with different biological behavior that are fatal in more than 40% of cases, due to their metastatic evolution and inadequate treatment options. ATR inhibition already showed an activity, even if modest, in broad pre-clinical models of STS. By using genome-wide CRISPR/Cas9 library screening, we identified ATM signaling network genes as critical drivers for resistance to the specific ATR inhibitor AZD6738. The role of such genes in resistance to AZD6738 was confirmed by using CRISPR/Cas9 knockout models. More strikingly, the ATM inhibitor AZD0156 works synergistically with AZD6738 in vitro and abolishes STS growth in vivo in our models of most frequent histotypes (such as dedifferentiated liposarcoma, leiomyosarcoma, and undifferentiated pleomorphic sarcoma among others). Moreover, the combination of AZD6738 and AZD0156 induced significantly higher levels of DNA damage than either drug used as single agent alone. In summary, our results demonstrate that targeting ATM is an effective approach to overcome resistance to ATR inhibition in different STS subtypes, including the most frequent histologies.

Inferring ligand-receptor cellular networks from bulk and spatial transcriptomic datasets with BulkSignalR

The study of cellular networks mediated by ligand-receptor interactions has attracted much attention recently owing to single-cell omics. However, rich collections of bulk data accompanied with clinical information exists and continue to be generated with no equivalent in single-cell so far. In parallel, spatial transcriptomic (ST) analyses represent a revolutionary tool in biology. A large number of ST projects rely on multicellular resolution, for instance the Visium™ platform, where several cells are analyzed at each location, thus producing localized bulk data. Here, we describe BulkSignalR, a R package to infer ligand-receptor networks from bulk data. BulkSignalR integrates ligand-receptor interactions with downstream pathways to estimate statistical significance. A range of visualization methods complement the statistics, including functions dedicated to spatial data. We demonstrate BulkSignalR relevance using different datasets, including new Visium liver metastasis ST data, with experimental validation of protein colocalization. A comparison with other ST packages shows the significantly higher quality of BulkSignalR inferences. BulkSignalR can be applied to any species thanks to its built-in generic ortholog mapping functionality.

Development and validation of novel prognostic models for zinc finger proteins-related genes in soft tissue sarcoma

As the most common transcriptional regulators, zinc finer proteins (ZNFs) play vital roles in occurrence and progression of malignant tumors. Whereas, information regarding the roles of ZNFs in soft tissue sarcomas (STS) remains scarce. In this study, a comprehensive bioinformatics analysis investigating roles of ZNFs in STS was performed. Initially, we extracted raw datasets of differentially expressed ZNFs from GSE2719. Using a sequence of bioinformatics methods, we then investigated the prognostic significance, function, and molecular subtype of these differentially expressed ZNFs. In addition, CCK8 and plate clone formation assays were used to explore the effect of ZNF141 on STS cells. A total of 110 differentially expressed ZNFs were identified. Nine ZNFs (HLTF, ZNF292, ZNF141, LDB3, PHF14, ZNF322, PDLIM1, NR3C2, and LIMS2) were selected to establish an overall survival (OS) prediction model, and seven ZNFs (ZIC1, ZNF141, ZHX2, ZNF281, ZNHIT2, NR3C2, and LIMS2) were used to develop a progression-free survival (PFS) prediction model. Compared with patients with low-risk in the TCGA training and testing cohorts, as well as the GEO validation cohorts, patients with high-risk had poorer OS and PFS. Using nomograms constructed with the identified ZNFs predicting OS and PFS, we established a clinically useful model. Four distinct molecular subtypes with different prognostic and immune infiltration characteristics were identified. In vitro experiments showed that ZNF141 promoted the proliferation and viability of STS cells. In conclusion, ZNF-related models are useful as prognostic biomarkers, suggesting their potentials as therapeutic targets in STS. These findings will enable us to develop novel strategies treating STS, which will potentially improve outcomes of patients with STS.

Staging Systems and Nomograms for Soft Tissue Sarcoma

Reliable tools for prognosis prediction are crucially needed by oncologists so they can tailor individual treatments. However, the wide spectrum of histologies and prognostic behaviors of sarcomas challenges their development. In this field, nomograms could definitely better account for their granularity compared to the more widely used AJCC/UICC TNM staging system. Nomograms are predictive tools that incorporate multiple risk factors and return a numerical probability of a clinical event. Since the development of the first nomogram in 2002, several other nomograms have been built, either general, site-specific, histology-specific, or both. Recently, some new “dynamic” nomograms and prognostic tools have been developed, allowing doctors to “recalculate” a patient’s prognosis by taking into account the time since primary surgery, the event history, and the potential time-dependent effect of covariates. Due to these new tools, prognosis prediction is no longer limited to the time of the first computation but can be adapted and recalculated based on the occurrence (or not) of any event as time passes from the first computation. In this review, we aimed to give an overview of the available nomograms for STS and to help clinicians in the process of selecting the best tool for each patient.

Role of Imaging in Initial Prognostication of Locally Advanced Soft Tissue Sarcomas

BACKGROUND

Although imaging is central in the initial staging of patients with soft tissue sarcomas (STS), it remains underused and few radiological features are currently used in practice for prognostication and to help guide the best therapeutic strategy. Yet, several prognostic qualitative and quantitative characteristics from magnetic resonance imaging (MRI) and positron emission tomography (PET) have been identified over these last decades.

OBJECTIVE

After an overview of the current validated prognostic features based on baseline imaging and their integration into prognostic tools, such as nomograms used by clinicians, the aim of this review is to summarize more complex and innovative MRI, PET, and radiomics features, and to highlight their role to predict indirectly (through histologic grade) or directly the patients' outcomes.

Heritable defects in telomere and mitotic function selectively predispose to sarcomas

Cancer genetics has to date focused on epithelial malignancies, identifying multiple histotype-specific pathways underlying cancer susceptibility. Sarcomas are rare malignancies predominantly derived from embryonic mesoderm. To identify pathways specific to mesenchymal cancers, we performed whole-genome germline sequencing on 1644 sporadic cases and 3205 matched healthy elderly controls. Using an extreme phenotype design, a combined rare-variant burden and ontologic analysis identified two sarcoma-specific pathways involved in mitotic and telomere functions. Variants in centrosome genes are linked to malignant peripheral nerve sheath and gastrointestinal stromal tumors, whereas heritable defects in the shelterin complex link susceptibility to sarcoma, melanoma, and thyroid cancers. These studies indicate a specific role for heritable defects in mitotic and telomere biology in risk of sarcomas.

Distinct Cellular Origins and Differentiation Process Account for Distinct Oncogenic and Clinical Behaviors of Leiomyosarcomas

In leiomyosarcoma (LMS), a very aggressive disease, a relatively transcriptionally uniform subgroup of well-differentiated tumors has been described and is associated with poor survival. The question raised how differentiation and tumor progression, two apparently antagonist processes, coexist and allow tumor malignancy. We first identified the most transcriptionally homogeneous LMS subgroup in three independent cohorts, which we named 'hLMS'. The integration of multi-omics data and functional analysis suggests that hLMS originate from vascular smooth muscle cells and show that hLMS transcriptional program reflects both modulations of smooth muscle contraction activity controlled by MYOCD/SRF regulatory network and activation of the cell cycle activity controlled by E2F/RB1 pathway. We propose that the phenotypic plasticity of vascular smooth muscle cells coupled with MYOCD/SRF pathway amplification, essential for hLMS survival, concomitant with PTEN absence and RB1 alteration, could explain how hLMS balance this uncommon interplay between differentiation and aggressiveness.

Quantitative proteomic studies addressing unmet clinical needs in sarcoma

Sarcoma is a rare and complex disease comprising over 80 malignant subtypes that is frequently characterized by poor prognosis. Challenges in clinical management include uncertainties in diagnosis and disease classification, limited prognostic and predictive biomarkers, incompletely understood disease heterogeneity among and within subtypes, lack of effective treatment options, and limited progress in identifying new drug targets and novel therapeutics. Proteomics refers to the study of the entire complement of proteins expressed in specific cells or tissues. Advances in proteomics have included the development of quantitative mass spectrometry (MS)-based technologies which enable analysis of large numbers of proteins with relatively high throughput, enabling proteomics to be studied on a scale that has not previously been possible. Cellular function is determined by the levels of various proteins and their interactions, so proteomics offers the possibility of new insights into cancer biology. Sarcoma proteomics therefore has the potential to address some of the key current challenges described above, but it is still in its infancy. This review covers key quantitative proteomic sarcoma studies with findings that pertain to clinical utility. Proteomic methodologies that have been applied to human sarcoma research are briefly described, including recent advances in MS-based proteomic technology. We highlight studies that illustrate how proteomics may aid diagnosis and improve disease classification by distinguishing sarcoma histologies and identify distinct profiles within histological subtypes which may aid understanding of disease heterogeneity. We also review studies where proteomics has been applied to identify prognostic, predictive and therapeutic biomarkers. These studies traverse a range of histological subtypes including chordoma, Ewing sarcoma, gastrointestinal stromal tumors, leiomyosarcoma, liposarcoma, malignant peripheral nerve sheath tumors, myxofibrosarcoma, rhabdomyosarcoma, synovial sarcoma, osteosarcoma, and undifferentiated pleomorphic sarcoma. Critical questions and unmet needs in sarcoma which can potentially be addressed with proteomics are outlined.

Soft-tissue sarcoma in adults: Imaging appearances, pitfalls and diagnostic algorithms

This article provides an overview of the current knowledge regarding diagnostic imaging of patients with soft-tissue sarcomas, which is a heterogeneous group of rare mesenchymal malignancies. After an initial contextualization, diagnostic flow-chart based on initial radiological findings of soft-tissue masses (with specific focus on adipocytic soft-tissue tumors [STTs], hemorragic STTs and retroperitoneal STTs) are provided considering relevant results from novel researches, guidelines, and experts' viewpoints, with the aim to help radiologists and clinicians in their practice. Particularly, the central place of sarcoma reference centers in the diagnostic and therapeutic management is highlighted, as well as the pivotal role that radiologists should play to correctly identify patients with soft-tissue sarcoma at the initial stage of the disease. Indications and methods for performing imaging-guided biopsies are also discussed, as well as clues to improve soft-tissue sarcoma grading with conventional and quantitative imaging.

Proteomic profiling of canine fibrosarcoma and adjacent peritumoral tissue

Fibrosarcoma (FSA) are rare soft tissue tumors that display aggressive local behavior and invasive growth leading to high rates of tumor recurrence. While the low incidence in humans hampers detailed understanding of the disease, FSA are frequent in dogs and present potential models for the human condition. However, a lack of in-depth molecular characterization of FSA and unaffected peritumoral tissue (PTT) in both species impedes the translational potential of dogs. To address this shortcoming, we characterized canine FSA and matched skeletal muscle, adipose and connective tissue using laser-capture microdissection (LCM) and LC-MS/MS in 30 formalin-fixed paraffin embedded (FFPE) specimens. Principal component analysis of 3'530 different proteins detected across all samples clearly separates the four tissues, with several targets strongly differentiating tumor from all three PTTs. 25 proteins were exclusively found in tumor tissue in ≥80% of cases. Among these, CD68 (a macrophage marker), Optineurin (OPTN), Nuclear receptor coactivator 5 (NCOA5), RAP1GDS1 (Rap1 GTPase-GDP dissociation stimulator 1) and Stromal cell derived factor 2 like 1 (SDF2L1) were present in ≥90% of FSA. Protein expression across all FSA was highly homogeneous and characterized by MYC and TP53 signaling, hyperactive EIF2 and immune-related changes as well as strongly decreased oxidative phosphorylation and oxidative lipid metabolism. Finally, we demonstrate significant molecular homology between canine FSA and human soft-tissue sarcomas, emphasizing the relevance of studying canine FSA as a model for human FSA. In conclusion, we provide the first detailed overview of proteomic changes in FSA and surrounding PTT with relevance for the human disease.

CINSARC signature outperforms gold-standard TNM staging and consensus molecular subtypes for clinical outcome in stage II-III colorectal carcinoma

The outcome of stage II-III colorectal cancer (CRC) is highly variable and therapeutic choice is currently based on TNM staging with a few additional biomarkers. However, studies show that some stage III patients have a better prognosis than some stage II patients. A promising consensus molecular (CMS) classification with prognostic relevance has been developed, but it is not used in daily practice. Our team developed CINSARC, a 67-gene expression prognostic signature, whose prognostic value has been demonstrated in many cancer types. It is applicable to formalin-fixed, paraffin-embedded (FFPE) blocks using NanoString® technology. We investigated whether it could predict outcome in stage II-III CRC. We established the CINSARC classification on the TCGA retrospective cohort comprising 297 stage II-III CRC patients using RNA sequencing and on a second independent cohort comprising 169 cases using NanoString® technology. We compared its recurrence-free and overall survival prognostic value with TNM staging and CMS classification. In the TCGA cohort, we showed that CINSARC significantly splits the population of stage II-III CRC into two groups with different progression-free interval (P = 1.68 × 10^-2; HR = 1.87 [1.11-3.16]) and overall survival (P = 3.73 × 10^-3; HR = 2.45 [1.31-4.59]) and is a strong prognostic factor in multivariate analysis, outperforming TNM staging and CMS classification. We validated these results in the second cohort by applying CINSARC on FFPE samples with Nanostring® technology. CINSARC is a ready-to-use tool with a robust independent prognostic value in stage II-III CRC.

The diagnosis, classification, and treatment of sarcoma in this era of artificial intelligence and immunotherapy

Soft-tissue sarcomas (STS) represent a group of rare and heterogeneous tumors associated with several challenges, including incorrect or late diagnosis, the lack of clinical expertise, and limited therapeutic options. Digital pathology and radiomics represent transformative technologies that appear promising for improving the accuracy of cancer diagnosis, characterization and monitoring. Herein, we review the potential role of the application of digital pathology and radiomics in managing patients with STS. We have particularly described the main results and the limits of the studies using radiomics to refine diagnosis or predict the outcome of patients with soft-tissue sarcomas. We also discussed the current limitation of implementing radiomics in routine settings. Standard management approaches for STS have not improved since the early 1970s. Immunotherapy has revolutionized cancer treatment; nonetheless, immuno-oncology agents have not yet been approved for patients with STS. However, several lines of evidence indicate that immunotherapy may represent an efficient therapeutic strategy for this group of diseases. Thus, we emphasized the remarkable potential of immunotherapy in sarcoma treatment by focusing on recent data regarding the immune landscape of these tumors. We have particularly emphasized the fact that the development of immunotherapy for sarcomas is not an aspect of histology (except for alveolar soft-part sarcoma) but rather that of the tumor microenvironment. Future studies investigating immunotherapy strategies in sarcomas should incorporate at least the presence of tertiary lymphoid structures as a stratification factor in their design, besides including a strong translational program that will allow for a better understanding of the determinants involved in sensitivity and treatment resistance to immune-oncology agents.

CSPG4 expression in soft tissue sarcomas is associated with poor prognosis and low cytotoxic immune response

Background

Soft tissue sarcomas (STS) are heterogeneous and pro-metastatic tumors. Identification of accurate prognostic factors and novel therapeutic targets are crucial. CSPG4 is a cell surface proteoglycan with oncogenic functions. It recently emerged as a potential target for immunotherapy, including cell therapy based on CSPG4-specific chimeric antigen receptor (CAR)-redirected cytokine-induced killer lymphocytes (CSPG4-CAR.CIKs) in STS. However, expression of CSPG4 is poorly known in STS so far.

Methods

We analyzed CSPG4 gene expression in 1378 localized STS clinical samples, and searched for correlations with clinicopathological data, including disease-free survival (DFS), and with tumor immune features.

Results

CSPG4 expression was heterogeneous across samples. High expression was associated with younger patients’ age, more frequent undifferentiated pleomorphic sarcoma and myxofibrosarcoma pathological subtypes, more frequent internal trunk tumor site, and more CINSARC high-risk samples. No correlation existed with pathological tumor size and grade, and tumor depth. Patients with high CSPG4 expression displayed 49% (95% CI 42–57) 5-year DFS versus 61% (95% CI 56–68) in patients with low expression (p = 3.17E−03), representing a 49% increased risk of event in the “CSPG4-high” group (HR = 1.49, 95% CI 1.14–1.94). This unfavorable prognostic value persisted in multivariate analysis, independently from other variables. There were significant differences in immune variables between “CSPG4-high” and “CSPG4-low” tumors. The "CSPG4-low" tumors displayed profiles suggesting higher anti-tumor cytotoxic immune response and higher potential vulnerability to immune checkpoint inhibitors (ICI). By contrast, the "CSPG4-high" tumors displayed profiles implying an immune-excluded tumor microenvironment, potentially induced by hypoxia, resulting from an immature chaotic microvasculature, and/or the presence of contractile myofibroblasts.

Conclusions

Patients with “CSPG4-high” STS, theoretically candidate for CAR.CIKs, display shorter DFS and an immune environment unfavorable to vulnerability to CAR.CIKs, which could be improved by combining anti-angiogenic drugs able to normalize the tumor vasculature. By contrast, “CSPG4-low” STS are better candidates for immune therapy involving ICI.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03679-y.

The immune subtypes and landscape of sarcomas

Background

Considering the molecular heterogeneity of sarcomas and their immunologically quiet character, immunotherapy (e.g., immune checkpoint inhibitors) plays a viable role in only a subset of these tumors. This study aimed to determine the immune subtypes (IMSs) of sarcomas for selecting suitable patients from an extremely heterogeneous population.

Results

By performing consensus clustering analysis of the gene expression profiles of 538 patients with sarcomas in online databases, we stratified sarcomas into three IMSs characterized by different immune cell features, tumor mutational burdens (TMBs), gene mutations, and clinical outcomes. IMS1 showed an immune “hot” and immunosuppressive phenotype, the highest frequencies of CSMD3 mutation but the lowest frequencies of HMCN1 and LAMA2 mutations; these patients had the worst progression-free survival (PFS). IMS2 was defined by a high TMB and more gene mutations, but had the lowest frequency of MND1 mutations. IMS3 displayed the highest MDN1 expression level and an immune “cold” phenotype, these patients had the worst PFS. Each subtype was associated with different expression levels of immunogenic cell death modulators and immune checkpoints. Moreover, we applied graph learning-based dimensionality reduction to the immune landscape and identified significant intra-cluster heterogeneity within each IMS. Finally, we developed and validated an immune gene signature with good prognostic performance.

Conclusions

Our results provide a conceptual framework for understanding the immunological heterogeneity of sarcomas. The identification of immune-related subtypes may facilitate optimal selection of sarcoma patients who will respond to appropriate therapeutic strategies.

Integrative analysis of synovial sarcoma transcriptome reveals different types of transcriptomic changes

Background: Synovial sarcoma (SS) is a rare and aggressive cancer that can come from distinct soft tissue types including muscle and ligaments. However, the transcriptomic landscape of SS is still poorly understood. This study aimed to systematically dissect the changes in SS transcriptome from different perspectives.

Methods: We performed deep total RNA sequencing on ten paired Synovial sarcoma and tumor-adjacent tissues to systematically dissect the transcriptomic profile of SS in terms of gene expression, alternative splicing, gene fusion, and circular RNAs.

Results: A total of 2,309 upregulated and 1,977 downregulated genes were identified between SS and tumor-adjacent tissues. Those upregulated genes could lead to the upregulation of the cell cycle, ribosome, and DNA replication pathways, while the downregulated genes may result in the downregulation of a set of metabolic biological processes and signaling pathways. Moreover, 2,511 genes (including 21 splicing factors) were differentially alternative spliced, indicating that the deregulation of alternative splicing could be one important factor that contributes to tumorigenesis. Additionally, we identified the known gene fusions of SS18-SSX1/SSX2 as well as 11 potentially novel gene fusions. Interestingly, 49 circular RNAs were differentially expressed and their parental genes could function in muscle contraction and muscle system processes.

Conclusions: Collectively, our comprehensive dissection of the transcriptomic changes of SS from both transcriptional and post-transcriptional levels provides novel insights into the biology and underlying molecular mechanism of SS.

Prediction tools for the personalized management of soft-tissue sarcomas of the extremity

Prediction tools are instruments which are commonly used to estimate the prognosis in oncology and facilitate clinical decision-making in a more personalized manner. Their popularity is shown by the increasing numbers of prediction tools, which have been described in the medical literature. Many of these tools have been shown to be useful in the field of soft-tissue sarcoma of the extremities (eSTS). In this annotation, we aim to provide an overview of the available prediction tools for eSTS, provide an approach for clinicians to evaluate the performance and usefulness of the available tools for their own patients, and discuss their possible applications in the management of patients with an eSTS.Cite this article: Bone Joint J 2022;104-B(9):1011-1016.

Perioperative Adriamycin plus ifosfamide vs. gemcitabine plus docetaxel for high-risk soft tissue sarcomas: randomised, phase II/III study JCOG1306

Background

This randomised phase II/III trial aimed to determine whether perioperative chemotherapy with gemcitabine plus docetaxel (GD) is non-inferior to the standard Adriamycin plus ifosfamide (AI) in terms of overall survival (OS) in patients with soft tissue sarcoma (STS).

Methods

Patients with localised high-risk STS in the extremities or trunk were randomised to receive AI or GD. The treatments were repeated for three preoperative and two postoperative courses. The primary endpoint was OS.

Results

Among 143 enrolled patients who received AI (70 patients) compared to GD (73 patients), the estimated 3-year OS was 91.4% for AI and 79.2% for GD (hazard ratio 2.55, 95% confidence interval: 0.80–8.14, P = 0.78), exceeding the prespecified non-inferiority margin in the second interim analysis. The estimated 3-year progression-free survival was 79.1% for AI and 59.1% for GD. The most common Grade 3–4 adverse events in the preoperative period were neutropenia (88.4%), anaemia (49.3%), and febrile neutropenia (36.2%) for AI and neutropenia (79.5%) and febrile neutropenia (17.8%) for GD.

Conclusions

Although GD had relatively mild toxicity, the regimen—as administered in this study—should not be considered a standard treatment of perioperative chemotherapy for high-risk STS in the extremities and trunk.

Clinical trial registration

jRCTs031180003.

CINSARC in high-risk soft tissue sarcoma patients treated with neoadjuvant chemotherapy: Results from the ISG-STS 1001 study

BACKGROUND

The Complexity INdex in SARComas (CINSARC) is a transcriptional signature derived from the expression of 67 genes involved in mitosis control and chromosome integrity. This study aims to assess CINSARC value of in an independent series of high-risk patients with localized soft tissue sarcoma (STS) treated with preoperative chemotherapy within a prospective, randomized, phase III study (ISG-STS 1001).

PATIENTS AND METHODS

Patients with available pre-treatment samples, treated with 3 cycles of either standard (ST) preoperative or histotype-tailored (HT) chemotherapy, were scored according to CINSARC (low-risk, C1; high-risk, C2). The 10-year overall survival probability (pr-OS) according to SARCULATOR was calculated, and patients were classified accordingly (low-risk, Sarc-LR, 10-year pr-OS>60%; high-risk, Sarc-HR, 10-year pr-OS<60%). Survival functions were estimated using the Kaplan-Meier method and compared using log-rank test.

RESULTS

Eighty-six patients were included, 30 C1 and 56 C2, 49 Sarc-LR and 37 Sarc-HR. A low level of agreement between CINSARC and SARCULATOR was observed (Cohen's Kappa = 0.174). The 5-year relapse-free survival in C1 and C2 were 0.57 and 0.55 (p = 0.481); 5-year metastases-free survival 0.63 and 0.64 (p = 0.740); 5-year OS 0.80 and 0.72 (p = 0.460). The 5-year OS in C1 treated with ST and HT chemotherapy was 0.84 and 0.76 (p = 0.251) respectively; in C2 treated it was 0.72 and 0.70 (p = 0.349). The 5-year OS in Sarc-LR treated with S and HT chemotherapy was 0.80 and 0.82 (p = 0.502) respectively; in Sarc-HR it was 0.70 and 0.61 (p = 0.233).

CONCLUSIONS

Our results, although constrained by the small size of the series, suggest that CINSARC has weak prognostic power in high-risk, localized STS treated with neoadjuvant chemotherapy.

Molecular testing of rhabdomyosarcoma in clinical trials to improve risk stratification and outcome: A consensus view from European paediatric Soft tissue sarcoma Study Group, Children's Oncology Group and Cooperative Weichteilsarkom-Studiengruppe

Rhabdomyosarcomas (RMSs) are the most common soft tissue sarcomas in children/adolescents less than 18 years of age with an annual incidence of 1-2/million. Inter/intra-tumour heterogeneity raise challenges in clinical, pathological and biological research studies. Risk stratification in European and North American clinical trials previously relied on clinico-pathological features, but now, incorporates PAX3/7-FOXO1-fusion gene status in the place of alveolar histology. International working groups propose a coordinated approach through the INternational Soft Tissue SaRcoma ConsorTium to evaluate the specific genetic abnormalities and generate and integrate molecular and clinical data related to patients with RMS across different trial settings. We review relevant data and present a consensus view on what molecular features should be assessed. In particular, we recommend the assessment of the MYOD1-LR122R mutation for risk escalation, as it has been associated with poor outcomes in spindle/sclerosing RMS and rare RMS with classic embryonal histopathology. The prospective analyses of rare fusion genes beyond PAX3/7-FOXO1 will generate new data linked to outcomes and assessment of TP53 mutations and CDK4 amplification may confirm their prognostic value. Pathogenic/likely pathogenic germline variants in TP53 and other cancer predisposition genes should also be assessed. DNA/RNA profiling of tumours at diagnosis/relapse and serial analyses of plasma samples is recommended where possible to validate potential molecular biomarkers, identify new biomarkers and assess how liquid biopsy analyses can have the greatest benefit. Together with the development of new molecularly-derived therapeutic strategies that we review, a synchronised international approach is expected to enhance progress towards improved treatment assignment, management and outcomes for patients with RMS.